[Ontology-editors] small molecule metabolism

[Harold Drabkin]

a thought..

How about saying that these are the non-polymeric molecules found within 
a cell? (assuming we do not want to count di-peptides, di-nucleotides, 
or di-saccharides )?

hd

Chris Mungall wrote:
>
> On Apr 9, 2009, at 9:35 AM, Valerie Wood wrote:
>
>> Tanya Berardini wrote:
>>
>>>
>>>
>>> On Thu, Apr 9, 2009 at 8:48 AM, Chris Mungall <cjm at berkeleybop.org 
>>> <mailto:cjm at berkeleybop.org>> wrote:
>>>
>>>
>>>    On Apr 9, 2009, at 3:35 AM, Valerie Wood wrote:
>>>
>>>        It seems like there is a gap in the terminology of biology to
>>>        decribe "everything that is not a macromolecule molecule".
>>>        Maybe we should make one up....
>>>        Perhaps "small molecule metabolism" would be acceptable if it
>>>        is defined as "everything that is not a macromolucule" but
>>>        that is not an acceptable way of defining something is it?
>>>
>>>
>>>    Do we really need a term for it? Why not just ask for non-X
>>>    metabolism any time you're interested in metabolism of Ys where Ys
>>>    are not Xs
>>>
>>>    Granted tools can't do this yet but it's not hard given the
>>>    correct structures in the ontology, and we should perhaps be
>>>    working towards a situation where tools do support this
>>>
>>>
>>> I am partial to this approach.  Defining 'small molecule metabolism' 
>>> as everything that is not 'macromolecule metabolism' violates the 
>>> ontology design principle of positivity.  Why not just combine the 
>>> annotations from the terms that do cover what is desired and then 
>>> analyze those results?
>>>
>>> Tanya
>>>
>>
>> Its quite difficult  to do this during enrichment analysis.
>> I have seen  a number of times that   terms which would be 
>> classically termed "biochemical pathways" are enriched, bacause I see 
>> the annotations  in my data individually.
>> The enrichment tools don't show this  because the number of 
>> annotations to the individual  terms are not large enough. tThe 
>> parent term "cellular metabolic process" is not enriched because the 
>> effect is masked  by all of the other 3000 annotations to this term 
>> generated  mainly by the variouse types of macromolecule metabolic 
>> process i.e.DNA metabolic process, protein metabolic process etc.
>>
>> When you are analysisng whole genome datasets it isn't really 
>> practical to add and subtract processes and repeat enrichment (it 
>> gets way too complicated to process and report the results, as you 
>> would have to fiddle with the P-values for everything you did 
>> manually and then reintegrate it into your whole genome analysis)
>>
>> This isn't really a problem for me now because I worked around it, 
>> but I could only do this because I know what the problem was.
>>
>> I thought that other users may appreciate some sort of grouping term 
>> here for similar analyses- it just seems that there should be a term 
>> to group these processes in the same way that macromolecular 
>> metabolic processes are grouped. The fact is that if you have a bunch 
>> of genes enriched for low numbers of  various small 
>> metabolism/canonical biochemical pathway terms, this  enrichment 
>> would  most likely be overlooked.
>
> I agree with Tanya but understand the practical need for enrichment 
> analysis.
>
> I am envisioning a partial solution along the following lines:
>
> Just as we have goslims, we can have gofats. a gofat would live 
> outside the ontology and contain statements like
>
> GOFAT:1 small molecule metabolism = metabolism and not has_participant 
> chebi:macromolecule
>
> The reasoner would compute is_a parentage to the fat terms and create 
> a derived obo file. If the tool accepts OBOFs+GAFs then just give the 
> tool this obo file instead of the regular one.
>
> (note this only works for tools that allow you to input an obo file. 
> Some web-based tools may not give you the flexibility to substitute 
> anything other than the regular GO)
>
> This should work in your particular case, no need to keep re-analyzing 
> once you've defined your fat. We could even make the fat-derived obo 
> files available on the website, as we do for slims
>
> This solution isn't perfect as it requires the analyzer to know a 
> priori which may be useful grouping categories. Really the tool should 
> be able to do this. For example, for a particular dataset, "metabolism 
> with a molecule with an X side chain, missing a Y" may be enriched. 
> There are strategies for dealing with this - rule mining, or 
> pre-computing every possible cross-product. This will require a little 
> more know-how from tools developers.
>
>
>>
>> val
>>
>>
>>
>>
>>
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>>
>>
>>
>> -- 
>> The Wellcome Trust Sanger Institute is operated by Genome Research 
>> Limited, a charity registered in England with number 1021457 and a 
>> company registered in England with number 2742969, whose registered 
>> office is 215 Euston Road, London, NW1 2BE.
>
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